Power doppler imaging system and method with improved clutter suppression

ABSTRACT

A method of power Doppler imaging may include receiving a plurality of temporally sequential frames of wall-filtered power Doppler signals, wherein the plurality of temporally sequential frames includes at least one previously adjusted output frame. The method may further include adjusting at least one of the plurality of temporally sequential frames to produce an adjusted output frame and generating a power Doppler image based, at least in part, on the adjusted output frame. The adjusting may involve filtering the plurality of temporally sequential frames to suppress the high spatial frequency and high temporal frequency content to produce the adjusted output frame.

CROSS-REFERENCE TO PRIOR APPLICATIONS

This application is the U.S. National Phase application under 35 U.S.C.§ 371 of International Application No. PCT/EP2018/059720, filed on Apr.17, 2018, which claims the benefit of U.S. Provisional PatentApplication 62/491,310, filed on Apr. 28, 2017. These applications arehereby incorporated by reference herein.

This application relates to ultrasonic imaging and specifically toDoppler imaging systems and method which may be equipped with enhancedclutter suppression.

Existing ultrasound imaging system are operable to image in B-mode,producing grayscale images of the tissue or structures of the imagedanatomy, and are also typically operable to image in one or more Dopplermodes to provide information about moving particles (e.g., blood flow).For conventional color Doppler imaging, the system transmits ultrasoundpulses to the tissue and extracts blood flow information, such as phaseand velocity information and power information, based on the Dopplereffect. The Doppler signals are typically passed through a wall filterto suppress signals from moving tissue (also referred to as clutter).However conventional wall filters may not be able to adequately suppresstissue clutter, particularly when imaging low-velocity blood flow statesand thus improved techniques for clutter suppression may be desired.

SUMMARY

A method of power Doppler imaging may include receiving a plurality oftemporally sequential frames of wall-filtered power Doppler signals,wherein the plurality of temporally sequential frames includes at leastone previously adjusted output frame. The method may further includeadjusting at least one of the plurality of temporally sequential framesto produce an adjusted output frame and generating a power Doppler imagebased, at least in part, on the adjusted output frame. The adjusting mayinvolve filtering the plurality of temporally sequential frames toidentify low spatial frequency and high temporal frequency content andsuppressing the low spatial frequency and high temporal frequencycontent to produce the adjusted output frame. In some embodiments, thefiltering of the plurality of temporally sequential frames to identifylow spatial frequency and high temporal frequency content may involvepassing each of the plurality of temporally sequential frames through aspatial low-pass filter (e.g., a boxcar filter or another spatiallow-pass filter) and through a temporal high-pass filter. The temporalhigh-pass filter may be implemented in accordance with any knowntechnique such as by using a transfer function that is responsive to thechange from frame to frame. Thereby, at the output of the filteringoperation the low spatial frequency and high temporal frequency contentwill be identified and adjustment parameters (e.g., a gain adjustment, ablending coefficient, or other) may be computed for suppressing the lowspatial frequency and high temporal frequency content from at least oneof the temporally sequential frames (e.g., a current input frame). Theadjustment parameter(s) may be applied to the at least one of thetemporally sequential frames (e.g., a current input frame) to produceone or more adjusted frames and to subsequently produce power Dopplerimages based on the adjusted frame(s).

In some embodiments, the adjusting at least one of the plurality oftemporally sequential frames may include filtering each of the pluralityof temporally sequential frames to remove high spatial frequency contentfrom each of the temporally sequential frames and produce filteredframes having relatively low spatial frequency content, determining thetemporal responsiveness between the filtered frames for every spatiallocation in the frames, and adjusting the at least one of the pluralityof temporally sequential frame based on the temporal responsivenessbetween the filtered frames. In some embodiments, the filtering each ofthe plurality of temporally sequential frames comprises passing each ofthe plurality of temporally sequential frames through a spatial low-passfilter. In some embodiments, the spatial low-pass filters may be aboxcar filter.

In some embodiments, the determining the temporal responsiveness betweenthe filtered frames may include computing a change (for example, apercentage change or a fractional change, or simply a signal strengthdifference) in signal strength between the filtered frames for everypixel or voxel in the frames, and generating blending coefficients basedon the computed changes in signal strength. In some examples, instead ofusing blending coefficients, the signal strength may be directlyadjusted based on the computed change to produce the adjusted outputframe. That is, adjusting of the input frame in the context of thepresent disclosure may be accomplished by adjusting a gain, byweighting, or one or more blending operations as further describedbelow. The purpose of the adjustment may generally be to suppress thelow spatial frequency and high temporal frequency content from the inputframe and any suitable adjustment may be used to obtain that effect.

In some embodiments where blending is used, the generating of blendingcoefficients may include mapping the computed changes (e.g., percent,fractional, or simple difference in signal strength) for each pixel orvoxel to respective blending coefficients using a transfer function. Insome embodiments, the transfer function used may have a decay componentand a growth component. In some embodiments, the method may furtherinclude generating second blending coefficients, for example based on adifference of the signal strength between the filtered frames at everypixel or voxel in the frames, and the adjusting of the input frame maybe performed further using the second blending coefficients. As implied,the techniques described herein can be equally applicable totwo-dimensional (2D) data sets, e.g., pixel-by-pixel processing of 2Dimage frames, or it may be applied to three-dimensional (3D) data set,such as by performing the clutter suppression on 3D data frames. In someembodiments, the steps of the process may be performed in real time,i.e., during the acquisition of one or more of the temporally sequentialframes.

In further embodiments, the method may include blending the adjustedoutput frame with a corresponding echo frame to produce the powerDoppler image. The adjusted output frame may include signal powerinformation and the corresponding echo frame may include echo intensityinformation, and in some embodiments the blending of the adjusted outputframe with the corresponding echo frame may involve computing at leastone blending coefficient using at least one of the signal powerinformation or the echo intensity information from the respective frame.Any of the methods described herein may be embodied in non-transitorycomputer-readable medium comprising executable instructions and whichwhen executed cause a processor (e.g., a processor of an ultrasoundimaging system) to perform the method embodied therein.

An ultrasound imaging system in accordance with some embodiments hereinmay be communicatively coupled to a source of ultrasound echoes forgenerating power Doppler images. The system may include a wall filterconfigured to produce wall filtered Doppler signals responsive to theultrasound echoes, and at least one processor configured to process thewall filtered Doppler signals to produce power Doppler image data. Theprocessor may be configured to receive temporally sequential frames ofthe wall filtered Doppler signals, wherein the two temporally sequentialframes include at least one previously adjusted output frame, filter thetemporally sequential frames to identify low spatial frequency and hightemporal frequency content, suppress the low spatial frequency and hightemporal frequency content to produce an adjusted output frame, andgenerate power Doppler image data based, at least in part, on theadjusted output frame.

In some embodiments of the system, the processor may include at leastone spatial low-pass filter configured to remove high spatial frequencyinformation from the temporally sequential frames to produce blurredframes and the processor may be further configured to generate one ormore adjustment parameters based, at least in part, on the temporalresponsiveness of the blurred frames. In some embodiments, theadjustment parameter may be simply an adjustment to the gain or it maybe a blend parameter (e.g., blending coefficients, as further describedbelow). In some embodiments, the processor may be configured tocalculate a change in signal strength between the temporally sequentialframes for all pixels or voxels in the respective frames, and whereinthe one or more adjustment parameters include blending coefficientsbased at least in part on the based on the calculated changes in signalstrength. The spatial low-pass filter may be a boxcar filter or anothersuitable low pass filter in some embodiments. In some embodiments, theprocessor may be configured to pass the calculated changes in signalstrength through a transfer function to generate the blendingcoefficients, and wherein the transfer function comprises a decaycomponent and a growth component. In some embodiments of the system, theblending coefficients may be first blending coefficients generated basedon a fractional change in signal strength and the processor may befurther configured to generate second blending coefficients based on adifference of the signal strength between the two temporally sequentialframes, and adjust the current input frame further based on the secondblending coefficients.

In some embodiments of the system, the processor may be configured toblend the adjusted output frame with a corresponding echo frame toproduce the power Doppler image data. In some embodiments, the processormay be further configured to cause the display to display an ultrasoundimage including a B-mode image overlaid with the power Doppler imagedata. In further embodiments, the ultrasound system may include atransducer array configured to acquire the ultrasound echoes, and theprocessor may be operable to generate the power Doppler image data inreal time while acquiring the ultrasound echoes.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram of an ultrasound imaging system arranged inaccordance with some embodiments of the present disclosure.

FIG. 2 is a block diagram of signal processing components of anultrasound imaging system arranged in accordance with some embodimentsof the present disclosure.

FIG. 3A is an example of a flash suppression processor in accordancewith some embodiments of the present disclosure.

FIG. 3B is another example of a flash suppression processor inaccordance with some embodiments of the present disclosure.

FIG. 4 is a plot of an example transfer function which may be used by aflash suppression processor to generate blending coefficients inaccordance with some embodiments of the present disclosure.

FIGS. 5A and 5B are pictorial representations of blending processes inaccordance with some embodiments of the present disclosure.

FIG. 6 is a sequence of input and output images associated with a flashsuppression process in accordance with some embodiments of the presentdisclosure.

FIG. 7 is a flow diagram of a process for power Doppler imaging inaccordance with some embodiments of the present disclosure.

FIGS. 8A-8C are exemplary plots of blending coefficients and look-uptables for various blending stages of a display blending process inaccordance with some embodiments of the present disclosure.

DESCRIPTION

The following description of certain exemplary embodiments is merelyexemplary in nature and is in no way intended to limit the invention orits applications or uses. In the following detailed description ofembodiments of the present systems and methods, reference is made to theaccompanying drawings which form a part hereof, and in which are shownby way of illustration specific embodiments in which the describedsystems and methods may be practiced. These embodiments are described insufficient detail to enable those skilled in the art to practice thepresently disclosed systems and methods, and it is to be understood thatother embodiments may be utilized and that structural and logicalchanges may be made without departing from the spirit and scope of thepresent system. Moreover, for the purpose of clarity, detaileddescriptions of certain features will not be discussed when they wouldbe apparent to those with skill in the art so as not to obscure thedescription of the present system. The following detailed description istherefore not to be taken in a limiting sense, and the scope of thepresent system is defined only by the appended claims.

A conventional ultrasound imaging system which is capable of performDoppler imaging typically includes a wall filter in the Doppler signalpath. The wall filter is a high-pass filter used to reduce or eliminatethe high-amplitude, low-velocity echoes from vessel walls, oftenreferred to as wall thump. The frequency cut-off of the filter may beconfigurable, and, is often set in the range of 50-1600 Hz. Manyultrasound imaging systems may also be configured to perform powerDoppler imaging. In contrast to color (or colorflow) Doppler imagingwhich encodes estimates of the mean Doppler frequency shift at aparticular position in color, power Doppler imaging is a technique thatencodes the power of the Doppler signal in color. This parameter isfundamentally different from the mean frequency shift. While frequencyof the signal is determined by the velocity of the tracked particles(i.e., red blood cells), the power of the Doppler signal depends on theamount of blood present. Because power Doppler imaging may be used toprovide an image of a different property of blood flow, power Dopplerhas shown several key advantages over color Doppler, including highersensitivity to flow, better edge definition and depiction of continuityof flow. Power Doppler is therefore particularly useful for imagingsuperficial structures or small low flow vessels (e.g., capillary flow).

In Doppler imaging, flash artifacts often appear as a high intensitysignal which appear rapidly in the temporal dimension and have a lowspatial frequency. Conventional Doppler imaging relies on setting thewall filter in the Doppler signal path for flash artifact suppression.That is, to remove flash artifacts arising from tissue motion,conventional systems set the wall filter aggressively low and/or limitthe power of the Doppler signal that passes the wall filter. The reasonfor this is that the strength of signals associated with tissue istypically much stronger than the strength of signals associated withblood flow. Specifically, when imaging low-velocity blood flow stateswith conventional systems, the wall filter is typically set low allowingfor small Doppler shifted frequencies and their corresponding velocitiescaused by low-velocity blood flow to be seen and displayed. However, atlow wall filter settings that may be suitable for imaging anatomy withlow-flow states (e.g., relatively slower flow through the arterioles,veins, venules, or capillaries), Doppler shifts from tissue motionrelative to the transducer are often times not readily filtered out andthus appear as a flash artifact. An improved system and method for flashartifact suppression for power Doppler imaging may be desirable.

This present disclosure may provide an improved solution to flashsuppression in power Doppler imaging. In accordance with some examplesherein, an additional flash suppression processing circuit is includedin the power Doppler signal path to further reduce flash artifacts thatarise when imaging anatomy with low-flow states. The flash suppressionprocessing circuit (or simply flash suppression processor) may beconfigured to perform additional flash suppression (also referred to asclutter suppression) along the power Doppler signal path withoutaffecting phase and velocity estimation within the Doppler processor.The inventors have recognized that when imaging flow in a low-flow state(e.g., venous flow or peripheral flow), the vessels associated with suchlow-flow states have a relatively lower resistive index and thus appearas a constant signal as opposed to the pulsatile signal typical ofhigher-flow states (e.g., arterial flow). Furthermore, signals producedfrom low-flow state blood flow are also typically associated with arelatively high spatial frequency. To that end, a system according tothe present disclosure may include a spatiotemporal processing circuitwhich identifies, on a spatial regional basis, the change in intensityof a signal in two temporally sequential frames. As the change in signalintensity increases between the two temporally sequential frames, thesignal is categorized as flash, and the persistence coefficient isaltered adaptively in such a manner as to suppress the regional signalfrom the current frame and therefore suppress flash artifacts. Thetemporally sequential frames may be temporally consecutive frames, orthey may be frames that are temporally sequential but spaced apart byone or more intermediate frames. Examples according to the presentinvention take advantage of the differences in spatial and temporalcharacteristic as shown in Table 1 below.

Flow information differs from tissue clutter in that flow informationtends to be of high spatial frequency in the form of long, thinstructures while tissue clutter tends to be of low spatial frequencywhich fills the near entirety of the ROI. It was also observed that flowinformation and tissue clutter behaved differently in the temporaldimension. Flow, particularly in the low-flow, small blood vessels(which are the vessels of particular interest) tended to have a lowresistive index. This meant that flow generally remains constantthroughout the cardiac cycle, much like venous flow. In contrast,‘flash’ artifacts from tissue motion arising from the cardiac cycle havenot been dampened to the extent that blood vessels have. Tissue cardiacmotion is also not relegated to the small individual vessels but insteadfills the entire tissue organ. As such, it is possible to roughlyclassify low-flow blood vessels and tissue clutter with thecharacteristics shown in Table 1.

TABLE 1 Difference in spatial and temporal characteristics between bloodvessels and tissue. Low-flow blood vessels Tissue Spatial characteristicHigh-frequency Low-frequency Temporal characteristic Low-frequencyHigh-frequency

In accordance with principles of the present invention, spatial andtemporal adaptive persistence is used to suppress flash artifacts.Persistence generally refers to the averaging of Doppler shift estimatesfrom current and previous frames, and may interchangeably be referred toas frame averaging. The persistence controls are used to select thelevel of smoothing or frame averaging for the image display. Highpersistence is used for slow moving organs or objects of interestwhereas low persistence is required for fast moving regions of interestsuch as the heart or fetal heart. The flash suppression processdescribed herein may employ an infinite impulse response (IIR) stylefilter, which includes a feedback loop (e.g., uses the previouslyprocessed frame output from the filter as an input when processing acurrent frame). In this manner, the flash processing circuit describedadaptively blends regions from the two frames to generate an outputframe which contains flow information but with tissue flash componentsminimized. As such, tissue flash that spans greater than one input framewould not defeat the suppression process as compared to conventionaltemporal median filters that may be employed in existing power Dopplerimaging systems, which would typically be defeated in such a scenario.The IIR filter described herein adaptively decides the contributionsfrom two frames, which pixels to blend, and how much to blend.

FIG. 2 shows a block diagram of a flash suppression processor inaccordance with the present disclosure. The Flash suppression processormay be located on the Doppler signal path and operate on thespatial-temporal characteristics of the Doppler signal post wall-filterto produce an additionally de-cluttered output (also referred to asadjusted output) which may contain a flash corrected power signal. Thisoutput may be additionally, optionally blended with the echo signals(e.g., IQ demodulated signals) from the B-mode signal path to produce anenhanced power Doppler image, as will be further described. Beforediscussing components of an example flash suppression processor, anultrasound imaging system which may include a flash suppressionprocessor in accordance with embodiments of the present invention isdescribed with reference to FIG. 1

FIG. 1 shows a block diagram of an ultrasound imaging system 100constructed in accordance with the principles of the present disclosure.An ultrasound imaging system 100 according to the present disclosure mayinclude a transducer array 114, which may be included in an ultrasoundprobe 112, for example an external probe or an internal probe such as anintravascular ultrasound (IVUS) catheter probe. In other embodiments,the transducer array 114 may be in the form of a flexible arrayconfigured to be conformally applied to a surface of subject to beimaged (e.g., patient). The transducer array 114 is configured totransmit ultrasound waves and receive echoes responsive to theultrasound waves. A variety of transducer arrays may be used, e.g.,linear arrays, curved arrays, or phased arrays. The transducer array114, for example, can include a two dimensional array (as shown) oftransducer elements capable of scanning in both elevation and azimuthdimensions for 2D and/or 3D imaging. As is generally known, the axialdirection is the direction normal to the face of the array (in the caseof a curved array the axial directions fan out), the azimuthal directionis defined generally by the longitudinal dimension of the array, and theelevation direction is transverse to the azimuthal direction. Thetransducer array 114 may be coupled to a microbeamformer 116, which maybe located in the ultrasound probe 112, and which may control thetransmission and reception of signals by the transducer elements in thearray 114. In some embodiments, the microbeamformer 116 may control thetransmission and reception of signals by active elements in the array114 (e.g., an active subset of elements of the array that define theactive aperture at any given time).

In some embodiments, the microbeamformer 116 may be coupled, e.g., by aprobe cable or wirelessly, to a transmit/receive (T/R) switch 118, whichswitches between transmission and reception and protects the mainbeamformer 122 from high energy transmit signals. In some embodiments,for example in portable ultrasound systems, the T/R switch 118 and otherelements in the system can be included in the ultrasound probe 112rather than in the ultrasound system base, which may house the imageprocessing electronics. An ultrasound system base typically includessoftware and hardware components including circuitry for signalprocessing and image data generation as well as executable instructionsfor providing a user interface.

The transmission of ultrasonic pulses from the transducer array 114under control of the microbeamformer 116 is directed by the transmitcontroller 120, which may be coupled to the T/R switch 118 and thebeamformer 122. In some embodiments, the probe 112 and beamformer may becoupled using a parallel data link to enable the simultaneous, paralleldata transfer between the array and the base to enable the signalprocessing components to simultaneously receive data for multiple or allimage lines in a field of view, such as during ultrafast imaging. Thetransmit controller 120 may also be coupled to the user interface 124and receive input from the user's operation of a user controls. The userinterface 124 may include one or more input devices such as a controlpanel 152, which may include one or more mechanical controls (e.g.,buttons, encoders, etc.), touch sensitive controls (e.g., a trackpad, atouchscreen, or the like), and other known input devices.

Another function which may be controlled by the transmit controller 120is the direction in which beams are steered. Beams may be steeredstraight ahead from (orthogonal to) the transducer array 114, or atdifferent angles for a wider field of view. In some embodiments, thepartially beamformed signals produced by the microbeamformer 116 may becoupled to a main beamformer 122 where partially beamformed signals fromindividual patches of transducer elements may be combined into a fullybeamformed signal. The beamformed signals are coupled to processingcircuitry 150, which may include one or more processors (e.g., a signalprocessor 126, a B-mode processor 128, a Doppler processor 160, a vectorflow processor, and one or more image generation and processingcomponents 168) configured to produce an ultrasound image from thebeamformed signals (i.e., beamformed RF data).

The signal processor 126 may be configured to process the receivedbeamformed RF data in various ways, such as bandpass filtering,decimation, I and Q component separation, and harmonic signalseparation. The signal processor 126 may also perform additional signalenhancement such as speckle reduction, signal compounding, and noiseelimination. The processed signals (also referred to as I and Qcomponents or IQ signals) may be coupled to additional downstream signalprocessing circuits for image generation. The IQ signals may be coupledto a plurality of signal paths within the system, each of which may beassociated with a specific arrangement of signal processing componentssuitable for generating different types of image data (e.g., B-modeimage data, Doppler image data, vector flow image data). For example,the system may include a B-mode signal path 158 which couples thesignals from the signal processor 126 to a B-mode processor 128 forproducing B-mode image data. The B-mode processor can employ amplitudedetection for the imaging of structures in the body.

The signals produced by the B-mode processor 128 may be coupled to ascan converter 130 and/or a multiplanar reformatter 132. The scanconverter 130 may be configured to arrange the echo signals from thespatial relationship in which they were received to a desired imageformat. For instance, the scan converter 130 may arrange the echo signalinto a two dimensional (2D) sector-shaped format, or a pyramidal orotherwise shaped three dimensional (3D) format. The multiplanarreformatter 132 can convert echoes which are received from points in acommon plane in a volumetric region of the body into an ultrasonic image(e.g., a B-mode image) of that plane, for example as described in U.S.Pat. No. 6,443,896 (Detmer). A volume renderer 134 may generate an imageof the 3D dataset as viewed from a given reference point, e.g., asdescribed in U.S. Pat. No. 6,530,885 (Entrekin et al.).

In some embodiments, the system may include a Doppler signal path 162which couples the output from the signal processor 126 to a Dopplerprocessor 160. The Doppler processor 160 may be configured to estimatethe Doppler shift and generate Doppler image data. The Doppler imagedata may include color data which is then overlaid with B-mode (i.e.grayscale) image data for display. The Doppler processor 160 may beconfigured to filter out unwanted signals (i.e., noise or clutterassociated with non-moving tissue), for example using a wall filter. TheDoppler processor 160 may be further configured to estimate velocity andpower in accordance with known techniques. For example, the Dopplerprocessor may include a Doppler estimator such as an auto-correlator, inwhich velocity (Doppler frequency) estimation is based on the argumentof the lag-one autocorrelation function and Doppler power estimation isbased on the magnitude of the lag-zero autocorrelation function. Motioncan also be estimated by known phase-domain (for example, parametricfrequency estimators such as MUSIC, ESPRIT, etc.) or time-domain (forexample, cross-correlation) signal processing techniques. Otherestimators related to the temporal or spatial distributions of velocitysuch as estimators of acceleration or temporal and/or spatial velocityderivatives can be used instead of or in addition to velocityestimators. In some examples, the velocity and power estimates mayundergo further threshold detection to further reduce noise, as well assegmentation and post-processing such as filling and smoothing. Thevelocity and power estimates may then be mapped to a desired range ofdisplay colors in accordance with a color map. The color data, alsoreferred to as Doppler image data, may then be coupled to the scanconverter 130, where the Doppler image data may be converted to thedesired image format and overlaid on the B-mode image of the tissuestructure to form a color Doppler or a power Doppler image.

In yet further examples, the system may include additional signalprocessing paths, such as a vector flow processing path, which couplesthe data from the signal processor 126 to a vector flow processor 154.The vector flow processor may be configured to extract angle-independentestimates of the velocity of flow through the imaged volume and map thevelocity information into a graphical representation (e.g., streamlineor pathlet-based visualization) of the velocity vector field. In someexample, the vector flow processor may be configured to estimate axialand lateral components of the flow velocity, and in examples where thesystem is operable to image a three-dimensional (3D) region of interest(ROI), to also estimate the elevational components of the flow velocityfor generating 2D or 3D velocity vector fields or maps. As with theB-mode and Doppler processors, vector flow imaging data may be coupledto the scan converter, multiplanar reformatter and/or volume rendererfor combining (e.g., overlaying) the vector flow imaging data with,e.g., B-mode image data to produce an overlay ultrasound imagedisplaying angle-independent velocity information concurrently with theassociated tissue structure.

Output (e.g., B-mode images, Doppler images, vector flow images) fromthe scan converter 130, the multiplanar reformatter 132, and/or thevolume renderer 134 may be coupled to an image processor 136 for furtherenhancement, buffering and temporary storage before being displayed onan image display 138. A graphics processor 140 may generate graphicoverlays for display with the images. These graphic overlays cancontain, e.g., standard identifying information such as patient name,date and time of the image, imaging parameters, and the like. For thesepurposes the graphics processor may be configured to receive input fromthe user interface 124, such as a typed patient name or otherannotations. In some embodiments, one or more functions of at least oneof the graphics processor, image processor, volume renderer, andmultiplanar reformatter may be combined into an integrated imageprocessing circuitry (the operations of which may be divided amongmultiple processor operating in parallel) rather than the specificfunctions described with reference to each of these components beingperformed by a discrete processing unit. Furthermore, while processingof the echo signals, e.g., for purposes of generating B-mode images orDoppler images are discussed with reference to a B-mode processor and aDoppler processor, it will be understood that the functions of theseprocessors may be integrated into a single processor. Referring now alsoto FIG. 2, a flash suppression processor 210 in accordance with someembodiments of the present disclosure.

FIG. 2 shows a block diagram of at least part of the processingcircuitry along the Doppler and B-mode signal paths 162 and 158,respectively. Along the Doppler signal path 162, signals (e.g., IQsignals received from the signal processor 126) are coupled to a Dopplerprocessor 260, which may initially pass the received signals through awall filter (e.g., a high-pass filter) to remove signals associated withstrong slower motion such as cardiac cycle tissue motion. The wallfiltered signals may then be provided, e.g., along parallel signal paths(e.g., 263 and 264), to a phase/velocity estimator 230 and to a powerestimator 232, which are configured to obtain flow information and powerinformation, respectively, from the Doppler signals. Phase/velocityestimate and power estimates may be obtained in accordance with any ofthe techniques described above with reference to FIG. 1 or any otherknown technique.

As shown in FIG. 2, the Doppler processor 260 may include a flashsuppression processor 210 which is arranged to perform additionalclutter suppression on the post wall filtered power Doppler signals,e.g., without affecting the Doppler signals that are used forphase/velocity estimates. An example flash suppression processor 210 mayinclude one or more buffers and one or more signal processing componentsincluding a spatial characteristic processing unit, a temporalcharacteristic processing unit, and a frame adjustment unit, which may,in some embodiments, be implemented by a blending map generation unitand a blending unit. The flash suppression unit 210 receives frames ofwall filtered Doppler signals, and specifically the power component ofthe Doppler signals. The frames may be temporarily stored in a buffer(e.g., frame buffer 212) until used by the signal processing componentsof the flash suppression processor 210. The frames are temporally andspatially processed such as to identify low spatial frequency and hightemporal frequency content, and one or more of the input frames areadjusted (e.g., blended or otherwise adjusted to suppress the lowspatial frequency and high temporal frequency content) to produce anadjusted output frame which may then be used for generating an enhancedpower Doppler image. While the spatial and temporal filtering isdescribed in a given sequence in this example, it will be understoodthat the order of the processing steps may be changed (e.g., reversed,such that the temporal filtering is performed before the spatialfiltering).

The spatial characteristic processing unit may be configured to receivethe wall filtered Doppler frames and spatially filter each frame toidentify low spatial frequency information, while removing high spatialfrequency content. The low-spatial frequency content, which may beindicative of tissue as shown in Table 1, will them be filtered furtherto identify regions (e.g., pixels or voxels) with content that varies inthe temporal dimension so as to identify tissue motion for subsequentsuppression. In some examples, the spatial characteristic processingunit may be implemented using a spatial low-pass filter 214 (alsoreferred to as clutter filter), which in some examples may be a boxcarfilter. For example, a 2D boxcar filter using a 2D sinc Fouriertransform may be used to filter out the high spatial frequencyinformation and pass the low spatial frequency information along thesignal path for further processing. As each frame is processed by thespatial filter 214, a blurred frame may be produced and the set of inputframes may then be coupled to the temporal characteristic processingunit for further processing. Other smoothing or bluffing filters may beused in other examples.

The temporal characteristic processing unit may be configured to receivetwo or more temporally sequential (for example, temporally consecutive)frames and identify regions with high temporal frequency information(i.e., regions or pixels rapidly changing in the temporal domain), whichmay be indicative of flash. The temporal characteristic processing unitmay be provided by a temporal high-pass filter configured to identifyframe content that varies from frame to frame, for example. In aspecific embodiment, discussed further below, the temporalresponsiveness between frames may be characterized by calculating thechange in signal strength (e.g., by calculating a percent change, afractional change, or difference between the signal strength in the twoor more blurred frames). Once frame content with low spatial frequencyand high temporal frequency has been identified, this content can thenbe further suppressed by adjusting at least one of the input frames(e.g., by blending, gain adjustments, or other) to produce an adjustedoutput frame. In some embodiments, the frame adjustment (e.g.,suppression of low spatial frequency and high temporal frequencycontent) may be made by a blending operation, as will be described infurther detail below. In such embodiments, the frame adjustment unit 217may be implemented using a blending map generation unit 218 and ablending processor 220. The output from the filtering steps may becoupled to the blending map generation unit, also referred to as mapgenerator 218.

The blending map generation unit (i.e., map generator 218) may beconfigured to generate a pixel by pixel map of blending or persistencecoefficient values (e.g., an alpha blending map and/or a beta blendingmap). The blending map generation unit 218 may pass the signal strengthchange values received from the temporal characteristic processing unitthrough a transfer function to map the signal strength change values toa blending or persistence coefficient value (e.g., ranging from 0-1) foreach pixel in the frame. A variety of transfer functions, for example alinear parabolic transfer function, may be used for generating thecoefficient map. The coefficient values may then be passed to a blendingunit to produce a compensated or flash suppressed output. In someembodiments, a plurality of blending maps may be produced to furtherenhance the blending process, as will be described e.g., with referenceto FIG. 3B. The blending map(s) generated by the blending map generationunit (i.e., map generator 218) are coupled to a blending unit, which isconfigured to provide the adjusted (or flash suppressed) output data. Inthe output from processor 210, low spatial frequency and high temporalfrequency content (e.g., consistent with tissue motion, as per Table 1)has been further suppressed and thus resulting power Doppler imagesgenerated using the adjusted output data may be of higher quality thanwould have been previously possible (e.g., simply using the data asfiltered by a conventional wall filter.

The adjusted output from the flash suppression processor 210 may becoupled to further downstream image processing (e.g., a scan converter,image and/or graphics processors, further blending processors, etc.) forgenerating a power Doppler image. In some embodiments, the power Dopplerdata output from flash suppression processor 210 may be blended fordisplay with the corresponding echo information (e.g., a B-mode imageframe received from the B-mode signal path 158) in a downstream blendingprocessor (also referred to as display blending processor 242), thefunctionality of which will be further described, for example withreference to FIGS. 8A-8C. The functionality of the display blendingprocessor 242 may be incorporated into the scan converter 240 or anotherone of the image generation and processing components of the ultrasoundsystem (e.g., processor 168 of system 100).

FIGS. 3A and 3B show examples of flash suppression units 300 and 300′ inaccordance with embodiments of the present invention. As describedherein, the flash suppression units 300 and 300′ include a spatialcharacteristic processing stage 301, a temporal characteristicprocessing stage 303, and a blending stage 305. In the spatialcharacteristic processing stage 301, spatial low pass filters 314 may beused to remove high spatial frequency content, while preserving the lowspatial frequency content, of each of the temporally sequential frames313-1 and 313-2 (e.g., labeled as output t−1 and input t, respectively,in the illustrated example). In the temporal characteristic processingstage 303, one or more regions (e.g., one or more pixels in the frame)that include high temporal frequency content may be identified and atleast one map which captures a temporal change in the signal isgenerated.

The operation of flash suppression units 300 and 300′ is now describedin further detail. At an example time t, the spatial low-pass filterreceives the current frame 313-2, denoted by input t, and the previousoutput frame 313-1, denoted by output t−1, as inputs. Each of the framesis filtered by a low-pass filter 314 to remove their high spatialfrequency content, while preserving low spatial frequency content. Inthis manner, high spatial frequency content associated with low-flowblood vessels is suppressed in accordance with the observations inTable 1. The low-pass filters 314 output blurred frames Blur t, labeledas 315-2 and Blur t−1, labeled as 315-1. In some embodiments, the lowpass filter 314 may be implemented using a 2D Boxcar filter. The 2Dboxcar filter, the filter size of which may be determined throughoptimization, is a relatively simple to implement blurring kernel and isthus one example of a filter that may be used. Other spatial low-passfilters may be used in other embodiments.

Next, a change in signal strength is computed for every spatial locationin the blurred frames Blurt and Blur t−1, as shown at block 316. Thecomputed change is used to provide information on the temporalcharacteristics (e.g., temporal responsiveness) of the signals at eachspatial location. The change in signal strength may be computed by:FractionalChange=(New−Old)/(New+Old), where the New corresponds to thesignal strength of the current input (e.g., input t) and Old correspondsto the signal strength of the previous input (e.g., output t−1). If Newand Old are both large, then FractionalChange would tend to be small dueto the denominator term. Compared to that, if New and Old are small,than the FractionalChange will tend to be larger for the same absolutedifference between New and Old. For example, if New=10 and Old=5, thenFractionalChange=0.333. It is noted that in some examples, thefractional change definition may be FractionalChange*100, however, inthis specific example the multiplication by 100 is excluded. For thesame numerator, if New=6 and Old=1, then FractionalChange=0.714. Thisbias for absolute values of New and Old may function well fordiscriminating between flow and tissue because post wall-filtered flowsignal tends to be large and relatively constant, while tissue flashtends to be strong in one frame but weak in another frame with overallsmaller values. FractionalChange tends to be larger for tissue flashcompared to flow for the same absolute difference between New and Old.

The computed change in signal strength may then be fed into a transferfunction to generate a first blending map (e.g., an Alpha map 318-1),which may be used by the blending processor 320 to produce output 313-3.In this manner, large changes in signal strength may be penalizedheavily in the Alpha map 318-1, which may serve to further discriminatebetween tissue and flow information according to Table 1. Since tissueflash arising from cardiac motion is of low spatial frequency, removinglow spatial frequency changes in signal intensity will further suppressflash in the output image.

In one example, an alpha map may be generated by a transfer function asshown in FIG. 4. The transfer function 400 in FIG. 4 is a piecewiseexponential function with an exponential decay and an exponential growthcurve portions 410 and 420, respectively. The decay portion of thefunction in this example is designed as the portion that will rejecttissue flash. A growth portion may be included in the transfer functionto improve performance of the flash suppression processor. Experimentaltesting revealed that large, continuous flash artifacts that arise dueto transducer motion may be treated as cardiac flash by the flashsuppression processor and could thus be continuously suppressed, whichmay result in image ‘freezing’ if the transducer is moved continuously.To avoid image “freezing” an exponential growth curve may be added torelax the suppression effect due to transducer motion. The transferfunction (also referred to herein as Alpha transfer function) may bedefined by the following equations:Decay=exp(−1*coef1*x)  (eq. 1),Growth=pow(x+coef3,coef2)  (eq. 2), andAlpha=min(max(Decay,Growth),1.0)  (eq. 3),

where x is the FractionalChange. According to this definition, Decayrepresents the decay portion 410 of the function (i.e., the downwardtrending curve) and is governed by coef1 which determines the rate ofexponential decay. Growth is the growth portion 420 (i.e., the upwardtrending portion of the curve) and is governed by coef3, which shiftsthe curve left or right, and coef2, which controls the rate ofexponential growth. The coefficients coef3 in the illustrated example isset to 0.4 and coef2 is set to 5, while coef1 may be determined byoptimization, e.g., in accordance with the principle that the higher thecoef1 is the more quickly it penalizes tissue flash. The coef2 and coef3may be set to other values in different embodiments of the presentdisclosure. Also, a variety of other transfer functions may be used,such as a linear parabolic transfer function, to map the signal strengthchange values to alpha values. The alpha values are provided to ablending processor 320 which generates the compensated output frame313-3 (e.g., output t, in this example). The Output frame may begenerated in accordance with the following equation:Output(t)=Alpha*(Input(t))+(1−Alpha)*Output(t−1)  (eq. 4),

which may also be referred to as an alpha blend equation which blendsthe current frame with the previous frame based on the Alpha value. Thealpha blend equation is also pictorially represented in FIG. 5A. Thepyramidal structure associated with each frame represents the differentspatial frequencies that may make up any given image frame. Blood flowfrom small vessels would be located in the high spatial frequency area(i.e., toward the top of the pyramidal structure), while tissue flashwould be located in the low spatial frequency region (i.e., towards thebottom of the pyramidal structure). Thus, the assumption made here isthat unwanted flash (i.e., tissue clutter), whether it is cardiac orotherwise, is of low spatial frequency, and therefore by subtracting outlow spatial frequency change between frames flash artifacts would besuppressed. While the alpha value is computed from the low spatialfrequency portion of the image, the blend is evenly applied to allspatial frequencies in the image. In some embodiments, performance maybe improved by a thresholding step. In some embodiments, the flashsuppression unit 300 may additionally optionally include a comparatorblock which compares the average power of Input t a power threshold. Ifthe average power is higher than the threshold, then a global gainsubtraction equivalent to the difference is introduced.

As described above, the alpha blend equation applies a singlepersistence coefficient to blend the two frames and produce the blendedor compensated frame. Performance of the flash suppression unit may befurther enhanced by the use of two blending maps, e.g., as shown in FIG.3B. The flash suppression processor 300′ in FIG. 3B may include some orall of the same components of flash suppression unit 300 and mayadditionally include a beta blend component 319, which generates a betablending map 318-2, e.g., to improve the performance of the flashsuppression unit as will be further described. Experimental testingincluding live scanning reveals that a blending step that uses a singlepersistence coefficient (e.g., an alpha blend equation) may produce sideeffects such as a laggy feeling and/or blurred blood flow speckle, whichmay be undesirable. Additionally, the alpha blending map and alpha blendequation may not sufficiently address flash that arises due totransducer motion. To address one or more of these problems, anadditional persistence coefficient may be computed and used in theblending process.

As shown in FIG. 3B, a beta blending map may be generated in accordancewith the following equation:Beta=ScalingFactor*(ΣInput(t)_(L)−1ΣOutput(t−1)_(L))  (eq. 5),

where Input(t)_(L) is the low frequency component of the input frame,and Output(t−1)_(L) is the low frequency component of the previousframe. Thus, the beta map may affect only the low frequency componentsof the image, based on the assumption that tissue flash is of lowspatial frequency. This is pictorially represented in FIG. 5B. In theillustration in FIG. 5B, the different spatial frequencies arepictorially shown using pyramidal structures. Here, Beta values arecalculated from low spatial frequency subbands. Output(t) is obtainedfrom Input(t) except for the low frequencies, which is computed from thedifference in low frequencies between Input(t) and Output(t−1) scaled bya scaling factor.

Referring again to FIG. 3B, blending unit 320′ may produce an outputusing the alpha and beta blend values, in accordance with the followingblend equation:Output(t)=Alpha*(Input(t)−Beta)+(1−Alpha)*Output(t−1)  (eq. 6),

where the Alpha values and Beta values are obtained from bloc318-1 and318-2, respectively. Therefore, computing a difference between blurredframes Blur t and Blur t−1 (weighted by signal strength change), theBeta map is passed into the blend to enhance tissue flash suppression.In some embodiments, a system may use only Beta values for flashsuppression. Also, while not shown in FIG. 3B, the flash suppressionunit 300′ may additionally, optionally include a comparator block 322for performing power thresholding as previously described.

FIG. 6 shows an example set of input images and the resulting outputimages after undergoing the flash suppression in accordance with theexamples herein. In the illustrated example, frames 413-1 and 413-2 areinput frames into flash suppression unit 300′, whereby regions of theimage that experience large positive changes in intensity are suppressedby persisting data from the previous image, while regions with low ornegative changes in intensity are not suppressed. The adjusted outputframe 413-3 and the next frame 413-4 are then input through the flashsuppression unit 330′ to produce the next adjusted frame 414-5, and soon. This process is repeated for each subsequent frame, which may occurin real time, e.g., during real-time image data acquisition. Thus, asillustrated, a system including a flash suppression unit in accordancewith any of the examples herein may be able to produce output images inwhich flash components in the image are suppressed while preserving flowinformation.

Referring back to the example in FIG. 2, additionally and optionally,the system may include a blending processor at the display generationstage (also referred to as display blending processor 242), which may beoperable to smoothly blend B-mode (or echo) data and Doppler (e.g.,power or velocity) data based on one or more Alpha blend values computedin accordance with the examples described further below. In addition,the blending processor at the display generation stage providesadditional flash artifact suppression. For example, in addition tosmoothly blending echo and flow data, this blending processor may alsoprovide some additional artifact removal since bright echoes seen inB-mode are often a source of tissue flash. The blend at this stage maywork to further suppress flash from these bright regions. In someembodiments, the display blending processor may include two blend stagesincluding a difference blend and a log power blend. Combining these twoblend stages may produce a more natural looking blended image. In otherembodiments, the blending processor 242 may include only one blend stage(e.g., the difference blend or lob power blend stage), as describedherein.

Difference Blend

During a difference blend, the display blending processor 242 evaluatesthe difference between the log power of color or power signal and thelog power of the echo signal and then computes the blend level based onthat difference, e.g., in accordance with the following equation:Alpha1=min[max[(ColorPowerVel−Echo+Offset)*Slope,0],255]  (eq. 7),

where ColorPowerVel is the value of the power/velocity data (in logunits) and echo is the value of the echo data (in log units). Offsetcontrols the hinge-point on which the blend occurs (in terms ofdifferences in signal strength between flow/power and echo) and Slopedetermines the rapidity that the blend occurs and the range (indifference values) that the blend occurs. In preferred embodiments,write priority may be applied. That is, if the echo signal value islarge compared to the power/flow signal, then priority will be given tothe echo data to be displayed. On the contrary, if the power/flow signalis large compared to the echo signal value, then the blend will bedominated by the flow signal data. Additionally, using this method ofblending will help suppress color on bright target artifacts as it istypically a highly echogenic reflector that causes the color artifact.Therefore, a strong echo reflector will push the blend to hide the flowsignal. FIG. 8A shows example Alpha1 values and a resulting 2D look uptable (LUT) for using the difference blend component. Notably, at lowlog blood values, the alpha values are not necessarily near zero whichleads to a blend that has blood flow colors even at very low flowvalues.

Log Power Blend

The second component of the blend is a log power blend based on the flowsignal strength:Alpha2=min[max[(ColorPowerVel−Offset2)*Slope2,0],255]  (eq. 8),

where ColorPowerVel again is the value of the power/velocity data (inlog units). Offset2 controls essentially the hinge-point on when theblend occurs and Slope2 determines the rapidity that the blend occursand the range (in difference values) that the blend occurs. That isduring a log power blend, the display blending processor 242 looks onlyat the color or power signal component without taking into effect theecho signal. FIG. 8B shows example Alpha2 values and a resulting 2D lookup table (LUT) for using the log power blend component. Notably, even atlow log blood values the blend will show echo values.

Combined Alpha and Blending Process

As described, in some embodiments, the display blending processor 242may include both blend stages and in such cases, the display blendingprocessor 242 may obtain a combined alpha value, e.g., in accordancewith the following equation:Alpha=(Alpha1/255)*(Alpha2/255)  (eq. 8).

By the use of the second blending stage and its resulting Alpha blendvalue, the two stage blending process may provide an improved blendingcontrol at low flow/power values. That is, at small colorPowerVel, thecombined blending value Alpha will largely be dominated towardsgrayscale since Alpha2 will be very small. At larger colorPowerVelvalues, Alpha will be determined largely by Alpha1. In otherembodiments, a weighting factor may be applied in combining the alphavalues from the two blend stages.

A combined blend may then be performed by the display blending processor242 on anti-logged echo and colorPower data in accordance with thefollowing equation:FinalOutput=log 2(anti log 2(ColorPowerVel)*Alpha+anti log2(echo)*(1−Alpha))

A blend using the above equation may provide a generally more naturalblended output as compared to blending using only one of the twocomponents or conventional techniques; although it is envision that forsimplicity some systems may not include both blending components. FIG.8C shows example Alpha values and a resulting 2D look up table (LUT) forusing the combined blending process. As shown, the combined blendedprocess may provide the benefit of writing echo data at very low flowvalues while retaining the comparison approach of the difference blendat larger blood values. While this two-stage blending process may beemployed in some embodiments, in other embodiments according to thepresent disclosure, the system may employ components for improved flashsuppression without using the two-stage blending process (e.g., usingconventional display blending techniques). Generally, any of theexamples herein may be used in combination with any other example of thepresent disclosure regardless of whether the specific combination wasexpressly illustrated or discussed.

FIG. 7 shows a flow diagram of an example process for power Dopplerimaging in accordance with the present disclosure. The process 700 mayinclude receiving temporally sequential frames (e.g., two or moreframes) of wall-filtered Doppler signals, as shown in block 710. In someembodiments, the additional cutter suppression may be performed usingtwo temporally sequential frames (e.g., temporally consecutive ortemporally sequential but spaced by intervening one or more frames) asinput. In other embodiments, the additional cutter suppression may beperformed using more than two sequential frames as input. In preferredembodiments, at least one of the input frames may be a previouslyadjusted frame so as to provide an infinite impulse response (IIR)filter. Each input frame may contain Doppler signals after the signalshave been filtered through a conventional wall filter that is typicallyused as part of the Doppler processor (i.e., to isolate blood flow fromtissue). However, as discussed, the wall filter may not be sufficient toremove all tissue clutter particularly in low flow applications.Depending on the imaging mode, the Doppler signals may be furtherprocessed within the Doppler processor, along either one of two paths,one configured for extracting flow information for the generation ofcolorflow Doppler images and one associated with extracting powerinformation for generating power Doppler images. Thus, additionally, andprior to providing the wall-filtered Doppler signals to the clutter orflash suppression processor, the Doppler signals may be processed toestimate the power or intensity of the signal and it is the powersignals (rather than the velocity/flow information) that are thencoupled to the clutter or flash suppression processor, as shown in block712.

The temporally sequential frames of Doppler signals are then processedin accordance with any of the embodiments of the present disclosure toidentify, as shown in block 714, low spatial frequency and high temporalfrequency content, which may be indicative of tissue clutter (e.g., asillustrated in Table 1). As further shown in block 716, the low spatialfrequency and high temporal frequency content is suppressed to producean adjusted output frame. Power Doppler image frames can then begenerated from power Doppler frames that include at least the adjustedoutput frame, e.g., as shown in block 718.

In some embodiments, the processing of the temporally sequential framesto identify low spatial frequency and high temporal frequency contentmay involve passing each of the temporally sequential frames through aspatial low-pass filter (e.g., a boxcar filter or any other type ofspatial low-pass filter) and then passing the spatially filtered frames(also referred to as blurred frames) through a temporal high-pass filterto identify rapidly changing content between the frames. In someembodiments, temporal high-pass filtering may be accomplished inaccordance with a variety of techniques such as by using a transferfunction that is responsive to the change from frame to frame. Forexample, a weighted sum of the frames may be used to identify hightemporal frequency content from the blurred frames, which can then beused to adjust the output frame (e.g., by adjusting a gain, generatingblending coefficients, or other adjustment method for suppressing theidentified low spatial frequency and high temporal frequency content.Thereby, in embodiments herein, at the output of the filtering operationthe low spatial frequency and high temporal frequency content will beidentified and adjustment parameters (e.g., a gain adjustment, ablending coefficient, or other) may be computed for suppressing the lowspatial frequency and high temporal frequency content from at least oneof the temporally sequential frames (e.g., a current input frame). Theadjustment parameter(s) may be applied to the at least one of thetemporally sequential frames (e.g., a current input frame) to produceone or more adjusted frames and to subsequently produce power Dopplerimages based on the adjusted frame(s).

In some embodiments, the temporal responsiveness between the filteredframes (e.g., rapid temporal variations between the blurred sequentialframes) may be determined by computing a change (for example, apercentage change or a fractional change, or simply a signal strengthdifference) in signal strength between the filtered frames. Thiscalculation may be performed at every pixel (for 2D frames) or voxel(for 3D frames) in the frames. Blending coefficients based on thecomputed changes in signal strength may be generated. Blendingcoefficients or other adjustment parameters may be obtained, forexample, based on a computed percent, fractional, or difference changein signal strength, which in some embodiments may be achieved using avariety of transfer functions. In one specific described example, atransfer function having a decay component and a growth component isused; however, the embodiments of the present disclosure are not limitedto that specific illustrated example. In some embodiments, the methodmay further include generating second blending coefficients, for examplebased on a difference of the signal strength between the filtered framesat every pixel or voxel in the frames, and the adjusting of the inputframe may be performed further using the second blending coefficients.As implied, the techniques described herein can be equally applicable totwo-dimensional (2D) data sets, e.g., pixel-by-pixel processing of 2Dimage frames, or it may be applied to three-dimensional (3D) data set,such as by performing the clutter suppression on 3D data frames. In someembodiments, the steps of the process may be performed in real time,i.e., during the acquisition of one or more of the temporally sequentialframes.

In some embodiments, instead of using blending coefficients, the signalstrength may be directly adjusted based on the computed change, forexample by adjusting a gain, or by weighting, or other suitableadjustment to suppress the low spatial frequency and high temporalfrequency content from the input frames and to produce an adjustedoutput frame. Power Doppler image frames may then be generated using atleast one adjusted output frame, e.g., as shown in block 718.

The process 700 may further include generating and displaying ultrasoundimages including the power Doppler information from the adjusted outputframe (e.g., an adjusted CPA frame) and corresponding echo information.When generating the image for display, the process may optionallyinclude a blending step in which the adjusted output frame is blendedwith a corresponding echo frame to produce the power Doppler image.Thus, in some embodiments, the method may further include, as shown inblocks 720 and 722, blending the adjusted output frame with acorresponding echo frame to produce the power Doppler image (e.g., thecombined or overlaid image in which the power Doppler frame is overlaidon the echo frame). The adjusted output frame may include signal powerinformation and the corresponding echo frame may include echo intensityinformation, and in some embodiments the blending of the adjusted outputframe with the corresponding echo frame may involve computing at leastone blending coefficient using at least one of the signal powerinformation or the echo intensity information from the respective frame.Any of the methods described herein may be embodied in non-transitorycomputer-readable medium comprising executable instructions and whichwhen executed cause a processor (e.g., a processor of an ultrasoundimaging system) to perform the method embodied therein.

The steps of the method may be repeated in real time while acquiring theultrasound signals so as to provide real-time power Doppler images on adisplay of a medical imaging system. For each repetition in thesequence, the adjusted output frame is used together with a new inputframe as inputs to the flash suppression process described herein,thereby providing an IIR type filtering process which utilizes the prioroutput as feedback and may thus provide improved performance overexisting flash suppression techniques.

In various embodiments where components, systems and/or methods areimplemented using a programmable device, such as a computer-based systemor programmable logic, it should be appreciated that the above-describedsystems and methods can be implemented using any of various known orlater developed programming languages, such as “C”, “C++”, “FORTRAN”,“Pascal”, “VHDL” and the like. Accordingly, various storage media, suchas magnetic computer disks, optical disks, electronic memories and thelike, can be prepared that can contain information that can direct adevice, such as a computer, to implement the above-described systemsand/or methods. Once an appropriate device has access to the informationand programs contained on the storage media, the storage media canprovide the information and programs to the device, thus enabling thedevice to perform functions of the systems and/or methods describedherein. For example, if a computer disk containing appropriatematerials, such as a source file, an object file, an executable file orthe like, were provided to a computer, the computer could receive theinformation, appropriately configure itself and perform the functions ofthe various systems and methods outlined in the diagrams and flowchartsabove to implement the various functions. That is, the computer couldreceive various portions of information from the disk relating todifferent elements of the above-described systems and/or methods,implement the individual systems and/or methods and coordinate thefunctions of the individual systems and/or methods described above.

In view of this disclosure it is noted that the various methods anddevices described herein can be implemented in hardware, software andfirmware. Further, the various methods and parameters are included byway of example only and not in any limiting sense. In view of thisdisclosure, those of ordinary skill in the art can implement the presentteachings in determining their own techniques and needed equipment toaffect these techniques, while remaining within the scope of theinvention. The functionality of one or more of the processors describedherein may be incorporated into a fewer number or a single processingunit (e.g., a CPU) and may be implemented using application specificintegrated circuits (ASICs) or general purpose processing circuits whichare programmed responsive to executable instruction to perform thefunctions described herein.

Although the present system may have been described with particularreference to an ultrasound imaging system, it is also envisioned thatthe present system can be extended to other medical imaging systemswhere one or more images are obtained in a systematic manner.Accordingly, the present system may be used to obtain and/or recordimage information related to, but not limited to renal, testicular,breast, ovarian, uterine, thyroid, hepatic, lung, musculoskeletal,splenic, cardiac, arterial and vascular systems, as well as otherimaging applications related to ultrasound-guided interventions.Further, the present system may also include one or more programs whichmay be used with conventional imaging systems so that they may providefeatures and advantages of the present system. Certain additionaladvantages and features of this disclosure may be apparent to thoseskilled in the art upon studying the disclosure, or may be experiencedby persons employing the novel system and method of the presentdisclosure. Another advantage of the present systems and method may bethat conventional medical image systems can be easily upgraded toincorporate the features and advantages of the present systems, devices,and methods.

Of course, it is to be appreciated that any one of the examples,embodiments or processes described herein may be combined with one ormore other examples, embodiments and/or processes or be separated and/orperformed amongst separate devices or device portions in accordance withthe present systems, devices and methods.

Finally, the above-discussion is intended to be merely illustrative ofthe present system and should not be construed as limiting the appendedclaims to any particular embodiment or group of embodiments. Thus, whilethe present system has been described in particular detail withreference to exemplary embodiments, it should also be appreciated thatnumerous modifications and alternative embodiments may be devised bythose having ordinary skill in the art without departing from thebroader and intended spirit and scope of the present system as set forthin the claims that follow. Accordingly, the specification and drawingsare to be regarded in an illustrative manner and are not intended tolimit the scope of the appended claims.

What is claimed is:
 1. A method of power Doppler imaging comprising:receiving a plurality of temporally sequential frames of wall-filteredpower Doppler signals, wherein the plurality of temporally sequentialframes includes at least one previously adjusted output frame; adjustingat least one of the plurality of temporally sequential frames, whereinthe adjusting includes: filtering the plurality of temporally sequentialframes to identify low spatial frequency and high temporal frequencycontent; and suppressing the low spatial frequency and high temporalfrequency content to produce an adjusted output frame; and generating apower Doppler image based, at least in part, on the adjusted outputframe.
 2. The method of claim 1, wherein the adjusting at least one ofthe plurality of temporally sequential frames includes: filtering eachof the plurality of temporally sequential frames to remove high spatialfrequency content from each of the temporally sequential frames andproduce filtered frames having relatively low spatial frequency content;determining the temporal responsiveness between the filtered frames forevery spatial location in the frames; and adjusting the at least one ofthe plurality of temporally sequential frame based on the temporalresponsiveness between the filtered frames.
 3. The method of claim 2,wherein the filtering each of the plurality of temporally sequentialframes comprises passing each of the plurality of temporally sequentialframes through a spatial low-pass filter.
 4. The method of claim 3,wherein the spatial low-pass filter is a boxcar filter.
 5. The method ofclaim 2, wherein determining the temporal responsiveness between thefiltered frames includes: computing a change in signal strength betweenthe filtered frames for every pixel or voxel in the frames; andgenerating blending coefficients based on the computed changes in signalstrength.
 6. The method of claim 5, wherein the generating blendingcoefficients includes mapping the computed changes for each pixel orvoxel to respective blending coefficients using a transfer function. 7.The method of claim 5, wherein the blending coefficients comprise firstblending coefficients computed based on a fractional change in signalstrength, the method further comprising: generating second blendingcoefficients based on a difference of the signal strength between thefiltered frames at every pixel or voxel in the frames, and applying thesecond blending coefficients to the at least one of the plurality oftemporally sequential frame to adjust the at least one of the pluralityof temporally sequential frame.
 8. The method of claim 1 furthercomprising blending the adjusted output frame with a corresponding echoframe to produce the power Doppler image.
 9. The method of claim 8,wherein the adjusted output frame includes signal power information andwherein the corresponding echo frame includes echo intensityinformation, and wherein the blending the adjusted output frame with thecorresponding echo frame includes computing at least one blendingcoefficient based on the at least one of the signal power information orthe echo intensity information from the respective frame.
 10. Anultrasound imaging system communicatively coupled to a source ofultrasound echoes, the system comprising: a wall filter configured toproduce wall filtered Doppler signals responsive to the ultrasoundechoes; and at least one processor configured to: receive temporallysequential frames of the wall filtered Doppler signals, wherein the twotemporally sequential frames include at least one previously adjustedoutput frame; filter the temporally sequential frames to identify lowspatial frequency and high temporal frequency content; suppress the lowspatial frequency and high temporal frequency content to produce anadjusted output frame; and generate power Doppler image data based, atleast in part, on the adjusted output frame.
 11. The ultrasound imagingsystem of claim 10, wherein the at least one processor includes at leastone spatial low-pass filter configured to remove high spatial frequencyinformation from the temporally sequential frames to produce blurredframes, and wherein the at least one processor is configured to generateone or more adjustment parameters based, at least in part, on thetemporal responsiveness of the blurred frames.
 12. The ultrasoundimaging system of claim 11, wherein the processor is configured tocalculate a change in signal strength between the temporally sequentialframes for all pixels or voxels in the respective frames, and whereinthe one or more adjustment parameters include blending coefficientsbased at least in part on the based on the calculated changes in signalstrength.
 13. The ultrasound imaging system of claim 11, wherein the atleast one processor is configured to pass the calculated changes insignal strength through a transfer function to generate the blendingcoefficients, and wherein the transfer function comprises a decaycomponent and a growth component.
 14. The ultrasound imaging system ofclaim 11, wherein the blending coefficients are first blendingcoefficients generated based on a fractional change in signal strength,and wherein the at least one processor is further configured to:generate second blending coefficients based on a difference of thesignal strength between the two temporally sequential frames; and adjustthe current input frame further based on the second blendingcoefficients.
 15. The ultrasound imaging system of claim 10, wherein theat least one processor is further configured to blend the adjustedoutput frame with a corresponding echo frame to produce the powerDoppler image data.